Introduction Metastatic involvement of groin nodes can alter radiation therapy planning for pelvic tumors. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) can identify nodal metastases; however, interpretation of PET/CT-positive nodes can be complicated by non-malignant processes. We evaluated quantitative metrics as methods to identify groin metastases in patients with pelvic tumors by comparison with standard subjective interpretive criteria, with pathology as the reference standard.
Methods We retrospectively identified patients with vulvar, vaginal, or anal cancers who underwent 18F-FDG PET/CT before pathologic evaluation of groin nodes between 2007 and 2017. Because patho-radiologic correlation was not possible for every node, one index node identified on imaging was selected for each groin. For each index node, standardized uptake value measurements, total lesion glycolysis, metabolic tumor volume, CT-based volume, and short and long axes were measured. Multivariate logistic regression was used to identify metrics predictive for pathologically positive groins and generate a probabilistic model. Area under the receiver-operating characteristic curves (AUCs) for the model were compared with clinical interpretation from the diagnostic report via a Wald’s χ2 test.
Results Of 55 patients identified for analysis, 75 groins had pathologic evaluation resulting in 75 index groin nodes for analysis with 35 groins pathologically positive for malignancy. Logistic regression identified mean standardized-uptake-value (50% threshold) and short-axis length as the most predictive imaging metrics for metastatic nodal involvement. The probabilistic model performed better at predicting pathologic involvement compared with standard clinical interpretation on analysis (AUC 0.91, 95% CI 0.84 to 0.97 vs 0.80, 95% CI 0.71 to 0.89; p<0.01).
Discussion Accuracy of 18F-FDG PET/CT for detecting groin nodal metastases in patients with pelvic tumors may be improved with the use of quantitative metrics. Improving prediction of nodal metastases can aid with appropriate selection of patients for pathologic node evaluation and guide radiation volumes and doses.
- vulvar and vaginal cancer
- lymph nodes
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Contributors SR participated in the design of the study, data acquisition, data analysis and drafted the manuscript. DF participated in the data acquisition and drafted the manuscript. TAD and LW performed the statistical analyses and drafted the manuscript. MG, CYH, YJR participated in data acquisition and drafted the manuscript. BAS, FD, DGM, MAP, JKS and PWG participated in data analysis and revised the manuscript. DLC and SM participated in the design of the study, data analysis and revised the manuscript. All authors read and approved the final manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests BAS has no relevant disclosures to this work, but reports serving in a consultant role for Curium Pharma, ImagingAB, Inc, and Progenics Pharmaceuticals, Inc, serving as advisory board member for GE Healthcare, and his spouse has received lecture honoraria from Siemens. DGM has no relevant disclosures to this work but reports speaking for Clovis and AstraZeneca. MAP has no relevant disclosures to this work but does report relationship with Merck, AstraZeneca, Tesaro, and Clovis Oncology. SM has no relevant disclosures but is supported by NIH K08 CA237822. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.
Patient consent for publication Not required.
Ethics approval This study was approved through the institutional review board with waived informed consent (HRPO#201707050).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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